When recording image data it is often helpful, for example for establishing a diagnosis, as well as in the training of doctors and personnel working in the medical sector, such as technicians who operate image recording modalities, to produce not just one image data volume but several image data volumes. This offers the advantage that information can be used from several or, in the most frequent case, two different volumes. For example, images of cerebral vessels can be captured in a first recording as image data volume A while in a further recording of image data the surrounding tissue or surrounding structures are recorded as a volume B. The image data volume showing the vessels then makes it possible for example to detect narrowing (stenosis) or widening (aneurysm) of the vessels. The surrounding tissue or the surrounding structures of the second volume make it possible to spatially assign information from the first volume data record.
For an optimal assignment of the information from the two data records to each other it is desirable to have a visualization which shows the data from the two volume data records in a single representation. Using such a representation pathologies could be detected and at the same time a spatial localization could be made. This has prompted attempts to visualize the two volume image data records in a merged representation, for which a certain fixed mixture ratio is set for the data from the two volumes. The problem is, however, that under certain circumstances some details of a first image data volume, which are important for example for making a diagnosis, are concealed by information from the second image data volume, which for example serves the purpose of spatial orientation. This can in certain circumstances lead to considerable deficiencies in the usability or the evaluation of the image data.